Forskning på informatikk

Informatikk omfatter et bredt spekter av emner. Vi har samlet ressursene og aktivitetene våre fra en så bred gruppe av emner i én gruppe, og i tillegg organiserer vi et sett med spesielle emneområder innenfor den større gruppen. Aktuelle spesialområder er listet opp nedenfor.

Forskningsgruppen for informatikk springer ut fra Institutt for realfag og industrisystemer på Kongsberg. Forskningsgruppen arbeider hovedsakelig med å kombinere grunnleggende og anvendt forskning for industrielle anvendelser.

Forskergruppen i informatikk tror på å kombinere undervisning og forskning for å oppnå fremragende kvalitet i både utdanning og forskning. Dette oppnås ved å involvere studenter i forskningsprosjekter, og ved å involvere industripartnere i utdanningsprogrammer, bachelor-, master-, industrimaster- og doktorgradsprogram. Forskningsgruppen støtter USNs pågående partnerskapsavtaler med en klynge av høyteknologiske selskaper.

Aktuelle forskningstemaer


Informatikk som fagfelt er involvert i de fleste moderne systemer. Anvendelsesområdene er uendelige. Bruksområdene er for det meste knyttet til industriapplikasjoner. Tidligere prosjekter har vært innen autonome systemer, katastrofehåndtering, dronekontroll, helseapplikasjoner og -styring, fjernstyrte laboratorier, flytrafikkontroll, kryptografi for skysikkerhet, cloudification av produksjon, cybersikkerhet for neste generasjons fabrikker, smarte byer og blockchain-applikasjoner.

Ekstern forskning?


Forskningsprosjekter ved USN innen informatikk er typisk anvendt og knyttet til industrien. Vi inviterer alle interesserte parter til å ta kontakt med oss for å utforske et mulig fremtidig samarbeid. Du kan enten bruke kontaktpersonen for et spesifikt område (som listet opp nedenfor) eller kontakte lederen for gruppen.

Forskningsinteresser


Datavitenskap er et bredt forskningsområde, og gruppen forsøker ikke å dekke alle områder. Forskningsgruppen dekker imidlertid et variert utvalg av temaområder.

Hovedtemaene, med en kontaktperson for hvert tema som for øyeblikket er identifisert som aktive i forskningsgruppen, er 

  • Maskinlæring, dyp læring og stordataanalyse og -håndtering. Vimala Nunavath
  • Cyberfysiske systemer og kontrollteori. Dag Samuelsen
  • Cybersikkerhet, kryptografi, sikkerhet i distribuerte systemer. Mohsen Toorani
  • Metamodellering, modellbasert integrasjon, semantikk og HCI. Vimala Nunavath
  • eLæring og fjernstyrte laboratorier. Olaf Hallan Graven
  • Rekonfigurerbar databehandling. Jose Ferreira
  • Semantisk datainteroperabilitet. Jan Dyre Bjerknes
  • Visualisering, utvidet virkelighet og spill. Olaf Hallan Graven

Pågående forskningsprosjekter

  • Education and training in 3D motion analysist (ETMO), 2022-2023.
  • Klinisk praksis på Madagaskar gir internasjonalt perspektiv på studiekvalitet og øyehelse, 2021-2025
  • Digital Security for “Co-created Health Technology (CoTecH)", 2022-2028.
Siste publikasjoner
  • Dugstad, J.H., et al., Kapasitetsbygging for digital helse og teknologi gjennom CoTecH - samskapt helseteknologi, in Norsk Sykepleierforbunds nasjonale e-helsekonferanse 2022 Inn i framtiden og forbi. 2022: Oslo.
  • Yari, Y., H. Nguyen, and T.V. Nguyen, Accuracy Improvement in Binary and Multi-Class Classification of Breast Histopathology Images, in 2020 IEEE Eighth International Conference on Communications and Electronics (ICCE). 2021, IEEE. p. 545.
  • Welzl, M., et al., Collaboration in the IETF: an initial analysis of two decades in email discussions, in Computer communication review. 2021. p. 29-32.
  • Welzl, M., et al., Transport Services: A Modern API for an Adaptive Internet Transport Layer. IEEE Communications Magazine, 2021. 59(4): p. 16-2242.
  • Toorani, M. and C. Gehrmann, A decentralized dynamic PKI based on blockchain, in SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing. 2021, Association for Computing Machinery (ACM). P. 1646-1655.
  • Olsson, C. and M. Toorani, A Permissioned Blockchain-based System for Collaborative Drug Discovery, in Proceedings of the 7th International Conference on Information Systems Security and Privacy (ICISSP’21), 2021. p. 121-132.
  • Nunavath, V., et al., Deep Learning for Classifying Physical Activities from Accelerometer Data. Sensors, 2021. 21(16): p. 28.
  • Nguyen, H.K., et al., as seeps in the Barents Sea – how does the geology influence the natural and well related seeps Energy-Efficient and Low Complexity Channel Coding for Wireless Body Area Networks, in 2018 5th NAFOSTED Conference on Information and Computer Science. 2021, UiT, The Arctic University of Norway IEEE. p. 80.
  • Nguyen, H., H.N. Dang, and T.V. Nguyen, Improve Uplink Achievable Rate for Massive MIMO Systems with Low-Resolution ADCs, in 2020 IEEE Eight International Conference on Communications and Electronics (ICCE). 2021: Phu Quoc.
  • Moholth, K., Smart Wearables: Challenges and Opportunities. Society for Design and Process Science, 2021: p. 56-59.
  • Langen, T., V. Nunavath, and O.H. Dahle, A Conceptual Framework Proposal for a Noise Modelling Service for Drones in U-Space Architecture. International Journal of Environmental Research and Public Health (IJERPH), 2021. 19(1): p. 20.
  • Gundersen, H. and S. Bos, Ternary computing; the future of IoT? Society for Design and Process Science, 2021: p. 43-47.
  • Ferreira, J., On the contribution of learning analytics to the quality of hybrid course delivery. Society for Design and Process Science, 2021: p. 27-30.
  • Dang, H.N., T.V. Nguyen, and H. Nguyen, Improve Uplink Achievable Rate for Massive MIMO Systems With Low-Resolution ADCs, in 2020 IEEE Eighth International Conference on Communications and Electronics (ICCE). 2021, IEEE. p. 545.
  • Dang, H.N., H. Nguyen, and T.V. Nguyen, Joint Detection and Decoding of Mixed-ADC Large-Scale MIMO Communication Systems with Protograph LDPC Codes. IEEE Access, 2021. 9: p. 101013-101029.
  • Bos, S., H.N. Risto, and H. Gundersen, High speed bi-directional binary-ternary interface with CNTFETS, in Smart Pervasive Computing (WSPC 2021). 2021.
  • Bjørk, J. and R. Juric, Teaching Software Development for Pervasive Computing Environment. Society for Design and Process Science, 2021: p. 23-26.
  • Asjad, S., et al., Software Architecture for Situation Awareness in Human-Machine Interactions for Applications in Humanitarian Emergencies. Society for Design and Process Science, 2021: p. 64-67.
  • Yari, Y., T.V. Nguyen, and H. Nguyen, Accuracy Improvement in Detection of COVID-19 in Chest Radiography, in 14th International Conference on Signal Processing and Communication Systems (ICSPCS). 2020, IEEE. p. 6.
  • Yari, Y., T.V. Nguyen, and H. Nguyen, Deep Learning Applied for Histological Diagnosis of Breast Cancer. IEEE Access, 2020. 8: p. 162432-162448.
  • Welzl, M., et al., Follow the Model: How Recursive Networking Can Solve the Internet's Congestion Control Problems, in 2020 International Conference on Computing, Networking and Communications (ICNC). 2020, IEEE conference proceedings. p. 518-524.
  • Vu, H.D., et al., On Design of Protograph LDPC Codes for Large-Scale MIMO Systems. IEEE Access, 2020. 8: p. 46017-46029.
  • Sanfilippo, F., T. Hua, and S. Bos, A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators, in 53rd Hawaii International Conference on System Sciences (HICSS 2020), Maui, Hawaii, United States of America. 2020. 2020: Maui, Hawaii.
  • Risto Nybø, H., S. Bos, and H. Gundersen, Automated synthesis of netlists for ternary-valued n-ary logic functions in CNTFET circuits, in The 61st SIMS Conference on Simulation and Modelling SIMS 2020. 2020: Virtual Conference.
  • Risto, H.N., S. Bos, and H. Gundersen, Automated synthesis of netlists for ternary-valued n-ary logic functions in CNTFET circuits. Linköping Electronic Conference Proceedings, 2020(176): p. 483-485.
  • Pfaff, J.B., E. Syverud, and D.A.H. Samuelsen, Predicting Thermal Losses in a Low-Energy Building. Linköping Electronic Conference Proceedings, 2020(176): p. 9-14.
  • Nhu, V.-H., et al., Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area. CATENA, 2020. 188: p. 13.
  • Nguyen, H., Y. Yasin, and N. Thuy, A State of the-art Deep Transfer Learning-Based Model for Accurate Breast Cancer Recognition in Histology Images, in IEEE Conference. 2020.
  • Nguyen, H., Y. Yari, and T.V. Nguyen, Accuracy Improvement in Detection of COVID-19 in Chest Radiography, in 2020 14th International Conference on Signal Processing and Communication Systems. 2020: Adelaide.
  • Moholth, K., O.C. Moholth, and J.D. Bjerknes, Computational Edge for Multiple Autonomous Objects, in 2020 IEEE International Conference on Human-Machine Systems (ICHMS). 2020, IEEE. p. 6.
  • Juric, R., K. Moholth, and K. Enger, Building Computationally Intensive Internet-of-Everything through Synergy of Engineering and Computer Science, in 2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC). 2020, IEEE. p. 300.
  • Hayes, D.A., et al., Online Identification of Groups of Flows Sharing a Network Bottleneck. IEEE/ACM Transactions on Networking, 2020. 28(5): p. 2229-2242.
  • Ferreira, J. and Z. Qureshi, Use of XR technologies to bridge the gap between higher education and continuing education. IEEE Global Engineering Education Conference, EDUCON, 2020. 2020: p. 913-918.
  • Bos, S., J.B. Nilsen, and H. Gundersen, Post-Binary Robotics: Using Memristors With Ternary States for Robotics Control, in 2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC). 2020, IEEE. p. 300.
  • Bos, S., et al., uMemristorToolbox: Open source framework to control memristors in Unity for ternary applications, in 2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL). 2020, IEEE Computer Society Digital Library: Miyazaki. p. 330.
  • Bos, S., J. Breivold Nilsen, and H. Gundersen, Post-Binary Robotics: Using Memristors With Ternary States for Robotics Control, in 8th Electronics System-Integration Technology Conference. 2020: Virtual Conference.
  • Bos, S., Keynote speaker: Descartes Dorm - The conscious computer, in Norwegian Research Days 2020. 2020: Bø.
  • Barik, R., et al., Performance Evaluation of In-network Packet Retransmissions using Markov Chains, in 2020 International Conference on Computing, Networking and Communications (ICNC). 2020, IEEE conference proceedings. p. 7.
  • Welzl, M., et al., Investigating the Delay Impact of the DiffServ Code Point (DSCP) On the Utility of Unregulated IP DiffServ Code Point (DSCP) Usage by End Systems, in Proceedings of the 2019 International Conference on Computing, Networking and Communications (ICNC): Green Computing, Networking, and Communications. 2019, IEEE Sarnoff Symposium. p. 612-616.
  • Vu, H.D., et al., Protograph LPDC Coded Large-Scale MIMO Communications With Low-Resolution ADCs A State-of-the-art Deep Transfer Learning-Based Model for Accurate Breast Cancer Recognition in Histology Images, in APCC 2019: 2019 25th Asia-Pacific Conference on Communications (APCC). 2019, IEEE. p. 540.
  • Sanfilippo, F., E. Helgerud, and S. Bos, Augmented Reality for Robotics Research, Education and Training, in Augmented Reality i opplæring. 2019: Kongsberg.
  • Pham, V.Q., et al., Performance of Deep Learning LDPC Coded Communications in Large Scale MIMO Channels, in NICS 2019: 2019 6th NAFOSTED Conference on Information and Computer Science (NICS). 2019, IEEE. p. 600.
  • Nunavath, V. and M. Goodwin, The Use of Artificial Intelligence in Disaster Management - A Systematic Literature Review, in 2019 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). 2019, IEEE conference proceedings.
  • Nguyen, T.V., et al., Performance Analysis of Protograph LDPC Codes Over Large-Scale MIMO Channels with Low-Resolution ADCs. IEEE Access, 2019. 7: p. 145145-145160.
  • Nguyen, T.V., H.N. Dang, and H. Nguyen, Delay-Limited Rate-Compatible Protograph LDPC Codes. International Journal of Engineering Trends and Technology, 2019. 67(7): p. 115-123.
  • Juric, R., K. Moholth, and O.C. Moholth, Detecting Cyber Security Vulnerabilities through Reactive Programming, in Proceeding of the 52nd Hawaii International Conference on System Sciences (HICSS 2019). 2019, AIS Electronic Library. p. 8000.
  • Jensen, M.G., et al., Towards an Artificial Pancreas: Software Architectural Model and Implementation for Personalized Insulin Administration Including pervasiveness and ubiquity into the HE curriculum: Experience from the USN, in Proceeding of the 52nd Hawaii International Conference on System Sciences (HICSS 2019). 2019, AIS Electronic Library Society for Design and Process Science. p. 8000.
  • Gupta, T., V. Nunavath, and S. Roy, CrowdVAS-Net: A deep-CNN based framework to detect abnormal crowd-motion behavior in videos for predicting crowd disaster. IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019. 2019-October: p. 2877-2882.
  • Gundersen, H., Ternary computing, in Foredrag for studenter og ansatte ved USN Kongsberg. 2019: Kongsberg.
  • Gundersen, H., From CMOS to CNTFET transistors, in Vitenskaplig foredrag for studenter og ansatte på NTNU Gjøvik. 2019: Gjøvik.
  • Bos, S., Why 3 is better than 2 (PechaKucha style), in Norwegian Research Days 2019. 2019: USN Campus Drammen.
  • Bos, S., Understanding the world with AI, in USN-TNM-Seminar Series. 2019: Kongsberg.
  • Bos, S., Ternary computing with memristors, in NTNU Seminar Series. 2019: Gjøvik.
  • Velvin, J., et al., Using Games for Learning to Improve Students Performance in Higher Education, in IEEE TALE 2018. 2018: Wollongong.
  • Sørli, J.-V. and O.H. Graven, Multi-Drone Framework for Cooperative Deployment of Dynamic Wireless Sensor Networks. Lecture Notes in Computer Science (LNCS), 2018. 10942 LNCS: p. 74-85.
  • Samuelsen, D.A.H. and O.H. Graven, A Holistic View on Engineering Education: How to Educate Control Engineers, in 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), proceedings of. 2018, IEEE. p. 1300.
  • Nunavath, V., et al., Deep Neural Networks for Prediction of Exacerbations of Patients with Chronic Obstructive Pulmonary Disease, in 19th International Conference on Engineering Applications of Neural Networks. 2018, Springer Publishing Company. p. 217-228.
  • Nguyen, T.V., C. Pham, and H. Nguyen, Delay-limited Protograph Low Density Parity Codes for Space-Time Block Codes, in 2018 IEEE 29th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). 2018, IEEE conference proceedings. p. 400.
  • Nguyen, T.V. and H. Nguyen, The Design of Low-Iteration Protograph Codes for Rayleigh Fading Channels with Spatial Diversity, in 2018 IEEE Seventh International Conference on Communications and Electronics (IEEE ICCE 2018). 2018, IEEE. p. 384.
  • Juric, R., K. Moholth, and O.C. Moholth, ANALYSING SOFTWARE VULNERABILITIES WITH REACTIVE PROGRAMMING. Society for Design and Process Science, 2018: p. 88-91.
  • Islam, S., et al., ctrlTCP: Reducing latency through coupled, heterogeneous multi-flow TCP congestion control, in IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). 2018, IEEE Communications Society. p. 214-219.
  • Islam, S., M. Welzl, and S. Gjessing, Lightweight and flexible single-path congestion control coupling, in NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. 2018, IEEE Communications Society. p. 1-6.
  • Graven, O.H., et al., An autonomous indoor exploration robot rover and 3D modeling with photogrammetry, in 2018 International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI-NCON 2018): Chiang Rai, Thailand 25 – 28 February 2018. 2018, IEEE. p. 188.
  • Boyd, C.A., et al., Security notions for cloud storage and deduplication. Lecture Notes in Computer Science (LNCS), 2018. 11192 LNCS: p. 347-365.
  • Boyd, C.A., et al., Definitions for Plaintext-Existence Hiding in Cloud Storage, in ARES'18. Proceedings of the 13th International Conference on Availability, Reliability and Security - Hamburg, Germany — August 27 - 30, 2018. 2018, Association for Computing Machinery (ACM).
  • Albrigtsen, S.I., et al., Neuroevolution of Actively Controlled Virtual Characters - An Experiment for an Eight-Legged Character A Multi-Layer Feed Forward Neural Network Approach for Diagnosing Diabetes, in 19th International Conference on Engineering Applications of Neural Networks. 2018, Springer Publishing Company IEEE conference proceedings. p. 94-105.
  • Abraham, A.K. and H. Nguyen, Overload Protection Using Artificial Intelligence for DC Motors. International Journal of Engineering Trends and Technology, 2018. 59(1): p. 6.
  • Toorani, M. and M. Toorani, How to stay safe online Hvor mye kan internett ødelegge for oss? 2017.
  • Toorani, M., Cryptography for Cloud Security, in Finse Winter School. 2017: Finse.
  • Sørli, J.-V., O.H. Graven, and J.D. Bjerknes, Multi-UAV Cooperative Path Planning for Sensor Placement Using Cooperative Coevolving Genetic Strategy, in The Eight International Conference On Swarm Intelligence. 2017: Fukuoka.
  • Nunavath, V., et al., Qualitative and Quantitative Study on Videotaped Data for Fire Emergency Response Representing fire emergency response knowledge through a domain modelling approach, in Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy - Proceedings of the 2016 International Conference on Leadership, Innovation and Entrepreneurship (ICLIE). 2017, Springer Publishing Company Norsk konferanse for organisasjoners bruk av informasjonsteknologi. p. 149-158.
  • Nunavath, V., A. Prinz, and T. Comes, Identifying First Responders Information Needs: Supporting Search and Rescue Operations for Fire Emergency Response. International Journal of Information Systems for Crisis Response and Management (IJISCRAM), 2017. 8(1): p. 25-46.
  • Nunavath, V. and A. Prinz, Visualization of Exchanged Information with Dynamic Networks: A Case Study of Fire Emergency Search and Rescue Operation, in Advance Computing Conference (IACC), 2017 IEEE 7th International. 2017, IEEE Press. p. 281-286.
  • Nunavath, V. and A. Prinz, Liferescue software prototype for supporting emergency responders during fire emergency response: A usability and user requirements evaluation. Lecture Notes in Computer Science (LNCS), 2017. 10272 LNCS: p. 480-498.
  • Nunavath, V. and A. Prinz, Data sources handling for emergency management: Supporting information availability and accessibility for emergency responders. Lecture Notes in Computer Science (LNCS), 2017. 10274 LNCS: p. 240-259.
  • Nunavath, V., V. Nunavath, and M. Goodwin, Model-Driven Data Integration for Emergency Response : Doctoral Dissertation for the Degree Philosophiae Doctor (PhD) at the Faculty of Engineering and Science, Specialization in Information and Communication Technology The Role of Artificial Intelligence in Social Media Big data Analytics for Disaster Management - Initial Results of a Systematic Literature Review, in 2018 5th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). 2017, Universitetet i Agder IEEE conference proceedings.
  • MacKinnon, L., et al., Integrating online learning into workplace information systems - supporting the goal of lifelong learning. Proceedings of the LACCEI international multi-conference for engineering, education and technology, 2017: p. 10.
  • Graven, O.H., et al., Managing Disasters–Rapid Deployment of Sensor Network from Drones, in 2017 2nd International Conference on Control and Robotics Engineering (ICCRE2017). 2017, IEEE. p. 184-188.
  • Boyd, C.A., et al., Secure Deduplication - Models and Optimization, in Distinguished Lectures Series in Cybersecurity. 2017: Darmstadt.
  • Barik, R., et al., fling: A Flexible Ping for Middlebox Measurements, in Teletraffic Congress (ITC 29), 2017 29th International. 2017, IEEE Communications Society. p. 134-142.
  • Armknecht, F., et al., Side channels in deduplication: trade-offs between leakage and efficiency, in ACM Asia Conference on Computer and Communications Security (ASIACCS'17). 2017, Association for Computing Machinery (ACM). p. 932.

Gruppeleder

Medlemmer

Ph.d.-kandidater

Eksterne medlemmer

  • Jan Dyre Bjerknes

Masterstudenter

  • Nikolai Olsen Eidheim 
  • Thomas Kaafjeld (Cybersecurity) 
  • Edvard Halmrast Lentz (Cybersecurity)
  • Sindre Kristoffersen Olsen (Cybersecurity) 

Tidligere masterstudenter

  • Sirajuddin Asjad (ansatt ved Kongsberg Defence & Aerospace)
  • Borgny Louise Gløersen (ansatt ved Guidant AS) 
  • Ali Haider (ansatt ved Applied Autonomy AS)
  • Saro Husaini 
  • Khandoker Tahmid Sami
  • Arnaf Aziz Torongo (ansatt ved Bring AS)

Samarbeidende institusjoner og forskningsnettverk